IgniWise Dataset — Prescribed Burn Window Prediction for Spain (1983–2015)

Machine learning dataset for predicting safe prescribed burn windows across 48 Spanish provinces, supporting the IgniWise open-source system. Dataset contents:- training_data.csv: 11,996 records derived from historical fire occurrence data (MITECO / IEPNB, 1983–2015) with 20 features including meteorological variables (statistically approximated from Spanish climate distributions), FWI indices (Van Wagner, 1987), and real geographic features per province- random_forest_v1.pkl: Trained Random Forest model (200 estimators, 5-fold CV accuracy: 99.5% ± 0.002)- provincias_geo.geojson: Spanish province geometries enriched with real topographic (Copernicus DEM GLO-30), vegetation (Sentinel-2 NDVI via GEE), and land cover features (CORINE Land Cover 2018) Note on meteorological features: weather variables in training_data.csv are statistical approximations calibrated to provincial climate. Operational predictions use real-time data from OpenWeatherMap. The 99.5% CV accuracy reflects model fit to the classification rules rather than independent real-world validation, which requires field data from executed prescribed burns. Sources: MITECO/IEPNB (fire occurrences), Copernicus DEM GLO-30 (topography),Sentinel-2/GEE (NDVI), CORINE Land Cover 2018 (vegetation cover).FWI methodology: Van Wagner, C.E. (1987), Canadian Forest Service. License: CC BY 4.0 | Web: igniwise.com | Code: github.com/TrueRomanZe/igniwise